{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:4FWQBP5NHEA2PJGB7NOGUGKVA5","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"1180b0c2f2e8dc1a677aac9819725f84dc0b0b592c81742b591fe45878e5c37f","cross_cats_sorted":["quant-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-03T20:41:30Z","title_canon_sha256":"01e31f17df3995b22bcfce4d9f870deaa9451d659dba63575e89b537b73b0a74"},"schema_version":"1.0","source":{"id":"2006.02516","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.02516","created_at":"2026-07-05T01:11:00Z"},{"alias_kind":"arxiv_version","alias_value":"2006.02516v2","created_at":"2026-07-05T01:11:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.02516","created_at":"2026-07-05T01:11:00Z"},{"alias_kind":"pith_short_12","alias_value":"4FWQBP5NHEA2","created_at":"2026-07-05T01:11:00Z"},{"alias_kind":"pith_short_16","alias_value":"4FWQBP5NHEA2PJGB","created_at":"2026-07-05T01:11:00Z"},{"alias_kind":"pith_short_8","alias_value":"4FWQBP5N","created_at":"2026-07-05T01:11:00Z"}],"graph_snapshots":[{"event_id":"sha256:313ae0d495851cd44bf58426df99dcc5cf5da1f5b1e198094c515fc89d58bebe","target":"graph","created_at":"2026-07-05T01:11:00Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2006.02516/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Originating from condensed matter physics, tensor networks are compact representations of high-dimensional tensors. In this paper, the prowess of tensor networks is demonstrated on the particular task of one-class anomaly detection. We exploit the memory and computational efficiency of tensor networks to learn a linear transformation over a space with dimension exponential in the number of original features. The linearity of our model enables us to ensure a tight fit around training instances by penalizing the model's global tendency to a predict normality via its Frobenius norm---a task that ","authors_text":"Chase Roberts, Guifre Vidal, Jinhui Wang, Stefan Leichenauer","cross_cats":["quant-ph","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-03T20:41:30Z","title":"Anomaly Detection with Tensor Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.02516","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:9f9a74b277400fa0895c8105d04e17b4b3dbee8b4c4e2ccbe58d18fa706a372f","target":"record","created_at":"2026-07-05T01:11:00Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"1180b0c2f2e8dc1a677aac9819725f84dc0b0b592c81742b591fe45878e5c37f","cross_cats_sorted":["quant-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-03T20:41:30Z","title_canon_sha256":"01e31f17df3995b22bcfce4d9f870deaa9451d659dba63575e89b537b73b0a74"},"schema_version":"1.0","source":{"id":"2006.02516","kind":"arxiv","version":2}},"canonical_sha256":"e16d00bfad3901a7a4c1fb5c6a1955074d853f8dafed3280b09b7867706258fc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e16d00bfad3901a7a4c1fb5c6a1955074d853f8dafed3280b09b7867706258fc","first_computed_at":"2026-07-05T01:11:00.485560Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:11:00.485560Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wlOs98Ra/gMLcHk477jRYDXHo7iadEGIu5Aqs9RYR1VBFa2TzO1BnzkCZoH0XCKs9Nb9aeGGiDnO8JNdCFYXCw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:11:00.486057Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.02516","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9f9a74b277400fa0895c8105d04e17b4b3dbee8b4c4e2ccbe58d18fa706a372f","sha256:313ae0d495851cd44bf58426df99dcc5cf5da1f5b1e198094c515fc89d58bebe"],"state_sha256":"142523e19b8f11d4721e5b4aeef14cb0d240449a2954cdb6749328fc789f2dc3"}